Learning Theory 17th Annual Conference on Learning Theory, COLT
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Learning Theory 17th Annual Conference on Learning Theory, COLT 2004 Banff, Canada, July 1-4, 2004 Proceedings
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Series Editors Jaime G. Carbonell, Carnegie Mellon University, Pittsburgh, PA, USA J¨org Siekmann, University of Saarland, Saarbr¨ucken, Germany Volume Editors John Shawe-Taylor University of Southampton ISIS Group, School of Electronics and Computer Science Southampton SO17 1BJ, UK E-mail: [email protected] Yoram Singer Hebrew University School of Computer Science and Engineering Givat-Ram campus, Jerusalem 91904, Israel E-mail: [email protected]
Library of Congress Control Number: 2004107575
CR Subject Classification (1998): I.2.6, I.2.3, I.2, F.4.1, F.2, F.1.1 ISSN 0302-9743 ISBN 3-540-22282-0 Springer-Verlag Berlin Heidelberg New York This work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, re-use of illustrations, recitation, broadcasting, reproduction on microfilms or in any other way, and storage in data banks. Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965, in its current version, and permission for use must always be obtained from Springer-Verlag. Violations are liable to prosecution under the German Copyright Law. Springer-Verlag is a part of Springer Science+Business Media springeronline.com c Springer-Verlag Berlin Heidelberg 2004 Printed in Germany Typesetting: Camera-ready by author, data conversion by PTP-Berlin, Protago-TeX-Production GmbH Printed on acid-free paper SPIN: 11016298 06/3142 543210
Preface
This volume contains papers presented at the 17th Annual Conference on Learning Theory (previously known as the Conference on Computational Learning Theory) held in Banff, Canada from July 1 to 4, 2004. The technical program contained 43 papers selected from 107 submissions, 3 open problems selected from among 6 contributed, and 3 invited lectures. The invited lectures were given by Michael Kearns on ‘Game Theory, Automated Trading and Social Networks’, Moses Charikar on ‘Algorithmic Aspects of Finite Metric Spaces’, and Stephen Boyd on ‘Convex Optimization, Semidefinite Programming, and Recent Applications’. These papers were not included in this volume. The Mark Fulk Award is presented annually for the best paper co-authored by a student. This year the Mark Fulk award was supplemented with two further awards funded by the Machine Learning Journal and the National Information Communication Technology Centre, Australia (NICTA). We were therefore able to select three student papers for prizes. The students selected were Magalie Fromont for the single-author paper “Model Selection by Bootstrap Penalization for Classification”, Daniel Reidenbach for the single-author paper “On the Learnability of E-Pattern Languages over Small Alphabets”, and Ran Gilad-Bachrach for the paper “Bayes and Tukey Meet at the Center Point” (co-authored with Amir Navot and Naftali Tishby). This year saw an ex
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